From cytogenetics to next-generation sequencing technologies: advances in the detection of genome rearrangements in tumorsThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Systems and Chemical Biology, and has undergone the Journal's usual peer review process

Accurate detection of copy number aberrations in FFPE samples using the mFAST-SeqS approach

BACKGROUND

Shallow whole genome sequencing (Shallow-seq) is used to determine the copy number aberrations (CNA) in tissue samples and circulating tumor DNA. However, costs of NGS and challenges of small biopsies ask for an alternative to the untargeted NGS approaches. The mFAST-SeqS approach, relying on LINE-1 repeat amplification, showed a good correlation with Shallow-seq to detect CNA in blood samples. In the present study, we evaluated whether mFAST-SeqS is suitable to assess CNA in small formalin-fixed paraffin-embedded (FFPE) tissue specimens, using vulva and anal HPV-related lesions.

METHODS

Seventy-two FFPE samples, including 36 control samples (19 vulva;17 anal) for threshold setting and 36 samples (24 vulva; 12 anal) for clinical evaluation, were analyzed by mFAST-SeqS. CNA in vulva and anal lesions were determined by calculating genome-wide and chromosome arm-specific z-scores in comparison with the respective control samples. Sixteen samples were also analyzed with the conventional Shallow-seq approach.

RESULTS

Genome-wide z-scores increased with the severity of disease, with highest values being found in cancers. In vulva samples median and inter quartile ranges [IQR] were 1[0-2] in normal tissues (n = 4), 3[1-7] in premalignant lesions (n = 9) and 21[13-48] in cancers (n = 10). In anal samples, median [IQR] were 0[0-1] in normal tissues (n = 4), 14[6-38] in premalignant lesions (n = 4) and 18[9-31] in cancers (n = 4). At threshold 4, all controls were CNA negative, while 8/13 premalignant lesions and 12/14 cancers were CNA positive. CNA captured by mFAST-SeqS were mostly also found by Shallow-seq.

CONCLUSION

mFAST-SeqS is easy to perform, requires less DNA and less sequencing reads reducing costs, thereby providing a good alternative for Shallow-seq to determine CNA in small FFPE samples.

Precision oncology: A primer for pediatric surgeons from the APSA cancer committee

Although most children with cancer can be cured of their disease, a subset of patients with adverse tumor types or biological features, and those with relapsed or refractory disease have significantly worse prognosis. Furthermore, current cytotoxic therapy is associated with significant late effects. Precision oncology, using molecular therapeutics targeted against unique genetic features of the patient's tumor, offers the potential to transform the multimodal therapy for these patients. Potentiated by advances in sequencing technology and molecular therapeutic development, and accelerated by large-scale multi-institutional basket trials, the field of pediatric precision oncology has entered the mainstream. These novel therapeutics have important implications for surgical decision making, as well as pre- and postoperative care. This review summarizes the current state of precision medicine in pediatric oncology including the active North American and European precision oncology clinical trials. LEVEL OF EVIDENCE: Treatment study Level V.

Functional genomics by integrated analysis of transcriptome of sweet potato (Ipomoea batatas (L.) Lam.) during root formation

BACKGROUND

Sweet potato is easily propagated by cuttings. But the molecular biological mechanism of adventitious root formation are not yet clear.

OBJECTIVE

To understand the molecular mechanisms of adventitious root formation from stem cuttings in sweet potato.

METHODS

RNA-seq analysis was performed using un-rooted stem (0 day) and rooted stem (3 days). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, comparison with Arabidopsis transcription factors (TFs) of DEGs were conducted to investigate the characteristics of genes and TFs involved in root formation. In addition, qRT-PCR analysis using roots at 0, 3, 6, 9, and 12 days after planting was performed to confirm RNA-seq reliability and related genes expression.

RESULTS

42,459 representative transcripts and 2092 DEGs were obtained through the RNA-seq analysis. The DEGs indicated the GO terms related to the single-organism metabolic process and cell periphery, and involved in the biosynthesis of secondary metabolites, and phenylpropanoid biosynthesis in KEGG pathways. The comparison with Arabidopsis thaliana TF database showed that 3 TFs (WRKY, NAC, bHLH) involved in root formation of sweet potato. qRT-PCR analysis, which was conducted to confirm the reliability of RNA-seq analysis, indicated that some metabolisms including oxidative stress and wounding, transport, hormone may be involved in adventitious root formation.

CONCLUSIONS

The detected genes related to secondary metabolism, some hormone (auxin, gibberellin), transports, etc. and 3 TFs (WRKY, NAC, bHLH) may have functions in adventitious roots formation. This results provide valuable resources for future research on the adventitious root formation of sweet potato.

Computational functional genomics-based approaches in analgesic drug discovery and repurposing

Persistent pain is a major healthcare problem affecting a fifth of adults worldwide with still limited treatment options. The search for new analgesics increasingly includes the novel research area of functional genomics, which combines data derived from various processes related to DNA sequence, gene expression or protein function and uses advanced methods of data mining and knowledge discovery with the goal of understanding the relationship between the genome and the phenotype. Its use in drug discovery and repurposing for analgesic indications has so far been performed using knowledge discovery in gene function and drug target-related databases; next-generation sequencing; and functional proteomics-based approaches. Here, we discuss recent efforts in functional genomics-based approaches to analgesic drug discovery and repurposing and highlight the potential of computational functional genomics in this field including a demonstration of the workflow using a novel R library ‘dbtORA’.

Current state of pediatric sarcoma biology and opportunities for future discovery: A report from the sarcoma translational research workshop

Sarcomas are a rare subgroup of pediatric cancers comprised of a variety of bone and soft-tissue tumors. While significant advances have been made in improving outcomes of patients with localized pediatric sarcomas since the addition of systemic chemotherapy to local control many decades ago, outcomes for patients with metastatic and relapsed sarcoma remain poor with few novel therapeutics identified to date. With the advent of new technologies to study cancer genomes, transcriptomes and epigenomes, our understanding of sarcoma biology has improved tremendously in a relatively short period of time. However, much remains to be accomplished in this arena especially with regard to translating all of this new knowledge to the bedside. To this end, a meeting was convened in Philadelphia, PA, on April 18, 2015 sponsored by the QuadW foundation, Children's Oncology Group and CureSearch for Children's Cancer that brought together sarcoma clinicians and scientists from North America to review the current state of pediatric sarcoma biology and ongoing/planned genomics based clinical trials in an effort to identify and bridge knowledge gaps that continue to exist at present. At the conclusion of the workshop, three key objectives that would significantly further our understanding of sarcoma were identified and a proposal was put forward to develop an all-encompassing pediatric sarcoma biology protocol that would address these specific needs. This review summarizes the proceedings of the workshop.

Overview of recurrent chromosomal losses in retinoblastoma detected by low coverage next generation sequencing

Genes are frequently lost or gained in malignant tumors and the analysis of these changes can be informative about the underlying tumor biology. Retinoblastoma is a pediatric intraocular malignancy, and since deletions in chromosome 13 have been described in this tumor, we performed genome wide sequencing with the Illumina platform to test whether recurrent losses could be detected in low coverage data from DNA pools of Rb cases. An in silico reference profile for each pool was created from the human genome sequence GRCh37p5; a chromosome integrity score and a graphics 40 Kb window analysis approach, allowed us to identify with high resolution previously reported non random recurrent losses in all chromosomes of these tumors. We also found a pattern of gains and losses associated to clear and dark cytogenetic bands respectively. We further analyze a pool of medulloblastoma and found a more stable genomic profile and previously reported losses in this tumor. This approach facilitates identification of recurrent deletions from many patients that may be biological relevant for tumor development.

Massively parallel tumor multigene sequencing to evaluate response to panitumumab in a randomized phase III study of metastatic colorectal cancer

PURPOSE

To investigate whether EGF receptor (EGFR) pathway mutations predicted response to monotherapy with panitumumab, an anti-EGFR monoclonal antibody, in a randomized phase III study of metastatic colorectal cancer.

EXPERIMENTAL DESIGN

Using massively parallel multigene sequencing, we analyzed 320 samples for 9 genes, with multigene sequence data from 288 (90%) samples.

RESULTS

Mutation rates were: KRAS (45%), NRAS (5%), BRAF (7%), PIK3CA (9%), PTEN (6%), TP53 (60%), EGFR (1%), AKT1 (<1%), and CTNNB1 (2%). In the randomized study and open-label extension, 22 of 138 (16%) wild-type KRAS (codons 12/13/61) patients versus 0 of 103 mutant KRAS (codons 12/13) patients had objective responses. Of 6 mutant KRAS (codon 61) patients, 1 with a Q61H mutation achieved partial response during the extension. Among wild-type KRAS (codons 12/13/61) patients, 0 of 9 patients with NRAS mutations, 0 of 13 with BRAF mutations, 2 of 10 with PIK3CA mutations, 1 of 9 with PTEN mutations, and 1 of 2 with CTNNB1 mutations responded to panitumumab. No patients responded to best supportive care alone. Panitumumab treatment was associated with longer progression-free survival (PFS) among wild-type KRAS (codons 12/13/61) patients [HR, 0.39; 95% confidence interval (CI), 0.28-0.56]. Among wild-type KRAS patients, a treatment effect for PFS favoring panitumumab occurred in patients with wild-type NRAS (HR, 0.39; 95% CI, 0.27-0.56) and wild-type BRAF (HR, 0.37; 95% CI, 0.24-0.55) but not mutant NRAS (HR, 1.94; 95% CI, 0.44-8.44).

CONCLUSIONS

These results show the feasibility and potential clinical use of next-generation sequencing for evaluating predictive biomarkers.

Gene Fusion Markup Language: a prototype for exchanging gene fusion data

Background

An avalanche of next generation sequencing (NGS) studies has generated an unprecedented amount of genomic structural variation data. These studies have also identified many novel gene fusion candidates with more detailed resolution than previously achieved. However, in the excitement and necessity of publishing the observations from this recently developed cutting-edge technology, no community standardization approach has arisen to organize and represent the data with the essential attributes in an interchangeable manner. As transcriptome studies have been widely used for gene fusion discoveries, the current non-standard mode of data representation could potentially impede data accessibility, critical analyses, and further discoveries in the near future.

Results

Here we propose a prototype, Gene Fusion Markup Language (GFML) as an initiative to provide a standard format for organizing and representing the significant features of gene fusion data. GFML will offer the advantage of representing the data in a machine-readable format to enable data exchange, automated analysis interpretation, and independent verification. As this database-independent exchange initiative evolves it will further facilitate the formation of related databases, repositories, and analysis tools. The GFML prototype is made available at http://code.google.com/p/gfml-prototype/.

Conclusion

The Gene Fusion Markup Language (GFML) presented here could facilitate the development of a standard format for organizing, integrating and representing the significant features of gene fusion data in an inter-operable and query-able fashion that will enable biologically intuitive access to gene fusion findings and expedite functional characterization. A similar model is envisaged for other NGS data analyses.

Inheritance model introduces differential bias in CNV calls between parents and offspring

Copy Number Variation (CNV) is increasingly implicated in disease pathogenesis. CNVs are often identified by statistical models applied to data from single nucleotide polymorphism panels. Family information for samples provides additional information for CNV inference. Two modes of PennCNV (the Joint-call and Posterior-call), which are some of the most well-developed family-based CNV calling methods, use a "Joint-model" as a main component. This models all family members' CNV states together with Mendelian inheritance. Methods based on the Joint-model are used to infer CNV calls of cases and controls in a pedigree, which may be compared to each other to test an association. Although benefits from the Joint-model have been shown elsewhere, equality of call rates in parents and offspring has not been evaluated previously. This can affect downstream analyses in studies that compare CNV rates in cases vs. controls in pedigrees. In this paper, we show that the Joint-model can introduce different CNV call rates among family members in the absence of a true difference. We show that the Joint-model may analytically introduce differential CNV calls because of asymmetry of the model. We demonstrate these differential call rates using single-marker simulations. We show that call rates using the two modes of PennCNV also differ between parents and offspring in one multimarker simulated dataset and two real datasets. Our results advise need for caution in use of the Joint-model calls in CNV association studies with family-based datasets.

Oncogenomics methods and resources

Today, cancer is viewed as a genetic disease and many genetic mechanisms of oncogenesis are known. The progression from normal tissue to invasive cancer is thought to occur over a timescale of 5-20 years. This transformation is driven by both inherited genetic factors and somatic genetic alterations and mutations, and it results in uncontrolled cell growth and, in many cases, death. In this article, we review the main types of genomic and genetic alterations involved in cancer, namely copy-number changes, genomic rearrangements, somatic mutations, polymorphisms, and epigenomic alterations in cancer. We then discuss the transcriptomic consequences of these alterations in tumor cells. The use of "next-generation" sequencing methods in cancer research is described in the relevant sections. Finally, we discuss different approaches for candidate prioritization and integration and analysis of these complex data.

Genomic restructuring in the Tasmanian devil facial tumour: chromosome painting and gene mapping provide clues to evolution of a transmissible tumour

Devil facial tumour disease (DFTD) is a fatal, transmissible malignancy that threatens the world's largest marsupial carnivore, the Tasmanian devil, with extinction. First recognised in 1996, DFTD has had a catastrophic effect on wild devil numbers, and intense research efforts to understand and contain the disease have since demonstrated that the tumour is a clonal cell line transmitted by allograft. We used chromosome painting and gene mapping to deconstruct the DFTD karyotype and determine the chromosome and gene rearrangements involved in carcinogenesis. Chromosome painting on three different DFTD tumour strains determined the origins of marker chromosomes and provided a general overview of the rearrangement in DFTD karyotypes. Mapping of 105 BAC clones by fluorescence in situ hybridisation provided a finer level of resolution of genome rearrangements in DFTD strains. Our findings demonstrate that only limited regions of the genome, mainly chromosomes 1 and X, are rearranged in DFTD. Regions rearranged in DFTD are also highly rearranged between different marsupials. Differences between strains are limited, reflecting the unusually stable nature of DFTD. Finally, our detailed maps of both the devil and tumour karyotypes provide a physical framework for future genomic investigations into DFTD.

The world's largest carnivorous marsupial, the Tasmanian devil, is threatened with extinction due to the emergence of devil facial tumour disease (DFTD), a fatal transmissible tumour. Critical loss of genetic diversity has rendered the devil vulnerable to transmission of tumour cells by grafting or transplanting the cells while biting and jaw wrestling. Initial studies of DFTD tumours revealed rearrangements among tumour chromosomes, with several missing chromosomes and four additional marker chromosomes of unknown origin. Since then, new strains of the disease have emerged and appear to be derived from the original strain. With no prior information available regarding the location of genes on normal devil chromosomes, a necessary first step towards characterisation of chromosome rearrangements in DFTD was to construct a map of the normal devil genome. This enabled us to elucidate the chromosome rearrangements in three DFTD strains. In doing so we determined the origin of the marker chromosomes and compared the three strains to determine which areas of the genome are involved in ongoing tumour evolution. Interestingly, rearrangements between strains are limited to particular genomic regions, demonstrating the unusual stability of this unique cancer. This study is therefore an important first step towards understanding the genetics of DFTD.

Marsupial genome sequences: providing insight into evolution and disease

Marsupials (metatherians), with their position in vertebrate phylogeny and their unique biological features, have been studied for many years by a dedicated group of researchers, but it has only been since the sequencing of the first marsupial genome that their value has been more widely recognised. We now have genome sequences for three distantly related marsupial species (the grey short-tailed opossum, the tammar wallaby, and Tasmanian devil), with the promise of many more genomes to be sequenced in the near future, making this a particularly exciting time in marsupial genomics. The emergence of a transmissible cancer, which is obliterating the Tasmanian devil population, has increased the importance of obtaining and analysing marsupial genome sequence for understanding such diseases as well as for conservation efforts. In addition, these genome sequences have facilitated studies aimed at answering questions regarding gene and genome evolution and provided insight into the evolution of epigenetic mechanisms. Here I highlight the major advances in our understanding of evolution and disease, facilitated by marsupial genome projects, and speculate on the future contributions to be made by such sequences.

De novo assembly and characterization of root transcriptome using Illumina paired-end sequencing and development of cSSR markers in sweet potato (Ipomoea batatas)

Background

The tuberous root of sweetpotato is an important agricultural and biological organ. There are not sufficient transcriptomic and genomic data in public databases for understanding of the molecular mechanism underlying the tuberous root formation and development. Thus, high throughput transcriptome sequencing is needed to generate enormous transcript sequences from sweetpotato root for gene discovery and molecular marker development.

Results

In this study, more than 59 million sequencing reads were generated using Illumina paired-end sequencing technology. De novo assembly yielded 56,516 unigenes with an average length of 581 bp. Based on sequence similarity search with known proteins, a total of 35,051 (62.02%) genes were identified. Out of these annotated unigenes, 5,046 and 11,983 unigenes were assigned to gene ontology and clusters of orthologous group, respectively. Searching against the Kyoto Encyclopedia of Genes and Genomes Pathway database (KEGG) indicated that 17,598 (31.14%) unigenes were mapped to 124 KEGG pathways, and 11,056 were assigned to metabolic pathways, which were well represented by carbohydrate metabolism and biosynthesis of secondary metabolite. In addition, 4,114 cDNA SSRs (cSSRs) were identified as potential molecular markers in our unigenes. One hundred pairs of PCR primers were designed and used for validation of the amplification and assessment of the polymorphism in genomic DNA pools. The result revealed that 92 primer pairs were successfully amplified in initial screening tests.

Conclusion

This study generated a substantial fraction of sweetpotato transcript sequences, which can be used to discover novel genes associated with tuberous root formation and development and will also make it possible to construct high density microarrays for further characterization of gene expression profiles during these processes. Thousands of cSSR markers identified in the present study can enrich molecular markers and will facilitate marker-assisted selection in sweetpotato breeding. Overall, these sequences and markers will provide valuable resources for the sweetpotato community. Additionally, these results also suggested that transcriptome analysis based on Illumina paired-end sequencing is a powerful tool for gene discovery and molecular marker development for non-model species, especially those with large and complex genome.

Analysis of next-generation genomic data in cancer: accomplishments and challenges

The application of next-generation sequencing technology has produced a transformation in cancer genomics, generating large data sets that can be analyzed in different ways to answer a multitude of questions about the genomic alterations associated with the disease. Analytical approaches can discover focused mutations such as substitutions and small insertion/deletions, large structural alterations and copy number events. As our capacity to produce such data for multiple cancers of the same type is improving, so are the demands to analyze multiple tumor genomes simultaneously growing. For example, pathway-based analyses that provide the full mutational impact on cellular protein networks and correlation analyses aimed at revealing causal relationships between genomic alterations and clinical presentations are both enabled. As the repertoire of data grows to include mRNA-seq, non-coding RNA-seq and methylation for multiple genomes, our challenge will be to intelligently integrate data types and genomes to produce a coherent picture of the genetic basis of cancer.

Reinventing diagnostics for personalized therapy in oncology

Human cancers are still diagnosed and classified using the light microscope. The criteria are based upon morphologic observations by pathologists and tend to be subject to interobserver variation. In preoperative biopsies of non-small cell lung cancers, the diagnostic concordance, even amongst experienced pulmonary pathologists, is no better than a coin-toss. Only 25% of cancer patients, on average, benefit from therapy as most therapies do not account for individual factors that influence response or outcome. Unsuccessful first line therapy costs Canada CAN$1.2 billion for the top 14 cancer types, and this extrapolates to $90 billion globally. The availability of accurate drug selection for personalized therapy could better allocate these precious resources to the right therapies. This wasteful situation is beginning to change with the completion of the human genome sequencing project and with the increasing availability of targeted therapies. Both factors are giving rise to attempts to correlate tumor characteristics and response to specific adjuvant and neoadjuvant therapies. Static cancer classification and grading systems need to be replaced by functional classification systems that not only account for intra- and inter- tumor heterogeneity, but which also allow for the selection of the correct chemotherapeutic compounds for the individual patient. In this review, the examples of lung and breast cancer are used to illustrate the issues to be addressed in the coming years, as well as the emerging technologies that have great promise in enabling personalized therapy.

Genomics of medulloblastoma: from Giemsa-banding to next-generation sequencing in 20 years

Advances in the field of genomics have recently enabled the unprecedented characterization of the cancer genome, providing novel insight into the molecular mechanisms underlying malignancies in humans. The application of high-resolution microarray platforms to the study of medulloblastoma has revealed new oncogenes and tumor suppressors and has implicated changes in DNA copy number, gene expression, and methylation state in its etiology. Additionally, the integration of medulloblastoma genomics with patient clinical data has confirmed molecular markers of prognostic significance and highlighted the potential utility of molecular disease stratification. The advent of next-generation sequencing technologies promises to greatly transform our understanding of medulloblastoma pathogenesis in the next few years, permitting comprehensive analyses of all aspects of the genome and increasing the likelihood that genomic medicine will become part of the routine diagnosis and treatment of medulloblastoma.

Applications of new sequencing technologies for transcriptome analysis

Transcriptome analysis has been a key area of biological inquiry for decades. Over the years, research in the field has progressed from candidate gene-based detection of RNAs using Northern blotting to high-throughput expression profiling driven by the advent of microarrays. Next-generation sequencing technologies have revolutionized transcriptomics by providing opportunities for multidimensional examinations of cellular transcriptomes in which high-throughput expression data are obtained at a single-base resolution.

Genomic rearrangements in BRCA1 and BRCA2: A literature review

Women with mutations in the breast cancer genes BRCA1 or BRCA2 have an increased lifetime risk of developing breast, ovarian and other BRCA-associated cancers. However, the number of detected germline mutations in families with hereditary breast and ovarian cancer (HBOC) syndrome is lower than expected based upon genetic linkage data. Undetected deleterious mutations in the BRCA genes in some high-risk families are due to the presence of intragenic rearrangements such as deletions, duplications or insertions that span whole exons. This article reviews the molecular aspects of BRCA1 and BRCA2 rearrangements and their frequency among different populations. An overview of the techniques used to screen for large rearrangements in BRCA1 and BRCA2 is also presented. The detection of rearrangements in BRCA genes, especially BRCA1, offers a promising outlook for mutation screening in clinical practice, particularly in HBOC families that test negative for a germline mutation assessed by traditional methods.

High-resolution mapping of copy-number alterations with massively parallel sequencing

Cancer results from somatic alterations in key genes, including point mutations, copy-number alterations and structural rearrangements. A powerful way to discover cancer-causing genes is to identify genomic regions that show recurrent copy-number alterations (gains and losses) in tumor genomes. Recent advances in sequencing technologies suggest that massively parallel sequencing may provide a feasible alternative to DNA microarrays for detecting copy-number alterations. Here we present: (i) a statistical analysis of the power to detect copy-number alterations of a given size; (ii) SegSeq, an algorithm to segment equal copy numbers from massively parallel sequence data; and (iii) analysis of experimental data from three matched pairs of tumor and normal cell lines. We show that a collection of approximately 14 million aligned sequence reads from human cell lines has comparable power to detect events as the current generation of DNA microarrays and has over twofold better precision for localizing breakpoints (typically, to within approximately 1 kilobase).

Applications of next-generation sequencing technologies in functional genomics

A new generation of sequencing technologies, from Illumina/Solexa, ABI/SOLiD, 454/Roche, and Helicos, has provided unprecedented opportunities for high-throughput functional genomic research. To date, these technologies have been applied in a variety of contexts, including whole-genome sequencing, targeted resequencing, discovery of transcription factor binding sites, and noncoding RNA expression profiling. This review discusses applications of next-generation sequencing technologies in functional genomics research and highlights the transforming potential these technologies offer.

Management of High-Throughput DNA Sequencing Projects: Alpheus

High-throughput DNA sequencing has enabled systems biology to begin to address areas in health, agricultural and basic biological research. Concomitant with the opportunities is an absolute necessity to manage significant volumes of high-dimensional and inter-related data and analysis. Alpheus is an analysis pipeline, database and visualization software for use with massively parallel DNA sequencing technologies that feature multi-gigabase throughput characterized by relatively short reads, such as Illumina-Solexa (sequencing-by-synthesis), Roche-454 (pyrosequencing) and Applied Biosystem's SOLiD (sequencing-by-ligation). Alpheus enables alignment to reference sequence(s), detection of variants and enumeration of sequence abundance, including expression levels in transcriptome sequence. Alpheus is able to detect several types of variants, including non-synonymous and synonymous single nucleotide polymorphisms (SNPs), insertions/deletions (indels), premature stop codons, and splice isoforms. Variant detection is aided by the ability to filter variant calls based on consistency, expected allele frequency, sequence quality, coverage, and variant type in order to minimize false positives while maximizing the identification of true positives. Alpheus also enables comparisons of genes with variants between cases and controls or bulk segregant pools. Sequence-based differential expression comparisons can be developed, with data export to SAS JMP Genomics for statistical analysis.